19 citations · 57 across the 9 of their papers we have counts for
9 papers
Data-efficient End-to-end Information Extraction for Statistical Legal Analysis
Wonseok Hwang, Saehee Eom, Hanuhl Lee +2
Legal practitioners often face a vast amount of documents. Lawyers, for instance, search for appropriate precedents favorable to their clients, while the number of legal precedents…
A Multi-Task Benchmark for Korean Legal Language Understanding and Judgement Prediction
Wonseok Hwang, Dongjun Lee, Kyoungyeon Cho +2
The recent advances of deep learning have dramatically changed how machine learning, especially in the domain of natural language processing, can be applied to legal domain. Howeve…
Semi-Structured Query Grounding for Document-Oriented Databases with Deep Retrieval and Its Application to Receipt and POI Matching
Geewook Kim, Wonseok Hwang, Minjoon Seo +1
Semi-structured query systems for document-oriented databases have many real applications. One particular application that we are interested in is matching each financial receipt i…
OCR-free Document Understanding Transformer
Geewook Kim, Teakgyu Hong, Moonbin Yim +7
Understanding document images (e.g., invoices) is a core but challenging task since it requires complex functions such as reading text and a holistic understanding of the document.…
BROS: A Pre-trained Language Model Focusing on Text and Layout for Better Key Information Extraction from Documents
Teakgyu Hong, Donghyun Kim, Mingi Ji +3
Key information extraction (KIE) from document images requires understanding the contextual and spatial semantics of texts in two-dimensional (2D) space. Many recent studies try to…
Cost-effective End-to-end Information Extraction for Semi-structured Document Images
Wonseok Hwang, Hyunji Lee, Jinyeong Yim +2
A real-world information extraction (IE) system for semi-structured document images often involves a long pipeline of multiple modules, whose complexity dramatically increases its…
Tractable loss function and color image generation of multinary restricted Boltzmann machine
Juno Hwang, Wonseok Hwang, Junghyo Jo
The restricted Boltzmann machine (RBM) is a representative generative model based on the concept of statistical mechanics. In spite of the strong merit of interpretability, unavail…
Syntactic Question Abstraction and Retrieval for Data-Scarce Semantic Parsing
Wonseok Hwang, Jinyeong Yim, Seunghyun Park +1
Deep learning approaches to semantic parsing require a large amount of labeled data, but annotating complex logical forms is costly. Here, we propose Syntactic Question Abstraction…
Spatial Dependency Parsing for Semi-Structured Document Information Extraction
Wonseok Hwang, Jinyeong Yim, Seunghyun Park +2
Information Extraction (IE) for semi-structured document images is often approached as a sequence tagging problem by classifying each recognized input token into one of the IOB (In…